{"id":"W4402011517","doi":"10.32604/iasc.2023.034029","title":"Ensemble Modeling for the Classification of Birth Data","year":2024,"lang":"en","type":"article","venue":"Intelligent Automation & Soft Computing","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; New Brunswick Innovation Foundation","keywords":"Ensemble learning; Computer science; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005106992,0.0008322686,0.001915213,0.001560466,0.0005363906,0.001048923,0.002246356,0.001263422,0.002870252],"category_scores_gemma":[0.01027109,0.0004391929,0.001776068,0.002064124,0.000393778,0.001679582,0.001181065,0.002449755,0.0009157752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006835926,"about_ca_system_score_gemma":0.0007352119,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01177838,"about_ca_topic_score_gemma":0.009781243,"domain_scores_codex":[0.9986594,0.000635787,0.00007795729,0.0002572295,0.0002192191,0.0001504416],"domain_scores_gemma":[0.9956201,0.002898769,0.0003204104,0.000444176,0.0006108772,0.0001056507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002347812,0.000131424,0.01105335,0.00009573857,0.0004390559,0.0001338163,0.0001749543,0.7794754,0.0005701243,0.02964035,0.007396735,0.1706543],"study_design_scores_gemma":[0.000002936811,0.00001188683,0.0004391486,0.000006220206,0.00001187314,0.00001123596,0.000006120192,0.9927666,0.00005641119,0.006288984,0.0003943638,0.000004155628],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04512234,0.002059941,0.9486903,0.0009516586,0.0002956256,0.00005717109,0.000891447,0.0005618081,0.001369781],"genre_scores_gemma":[0.823195,0.003204916,0.1564359,0.0003615907,0.0007308462,0.0004010529,0.004976035,0.0001790606,0.01051559],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01177838,"threshold_uncertainty_score":0.02700865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1318125959145786,"score_gpt":0.3785556182336461,"score_spread":0.2467430223190674,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}